000			01216nam a22002177a 4500
003			NULRC
005			20250211150827.0
008			250211b ph ||||| |||| 00| 0 eng d
040			_cNULRC
050			_aGSD CCIT PhDCS .A59 2024
100			_aAixiang, He _eauthor
245			_aResearch of sentiment tendency analysis of film reviews based based on deep learning / _cHe Aixiang
260			_aManila : _bNational University, _c2024
300			_axiv, 143 leaves ; _c28 cm.
504			_aIncludes bibliographical references.
505			_aChapter 1. Introduction -- Chapter 2. Theoretical Framework -- Chapter 3. Methodology -- Chapter 4. Results and Discussion -- Chapter 5. Summary, Conclusion and Recommendation -- References.
520			_aWith the development of the Internet+ pan-entertainment service platform, the cinema sector has established a system where consumers can buy tickets on the internet, watch movies in theaters and then share their reviews and feedback online, resulting in a large amount of film and review data, whose evaluation content fully reflects the attitude and views of moviegoers.
650			_aDEEP LEARNING
650			_aNATURAL LANGUAGE PROCESSING
942			_2lcc _cDIS _n0
999			_c1885 _d1885